Comparison of ground-based GPS precipitable water vapour to independent observations and Numerical Weather Prediction model reanalyses over Africa.
Bock, O. (1), M.-N. Bouin (2), A. Walpersdorf (3), J.P. Lafore (4), S. Janicot (5), F. Guichard (4), A. Agusti-Panareda (6)
Quart. J. Roy. Meteor. Soc.
,
133, 2011-2027, 2007

1 IPSL/SA, Université Paris VI, France

2 LAREG, IGN, France
3 LGIT, CNRS, France
4 CNRM/GMME, Météo-France, France
5 IPSL/LOCEAN, Université Paris VI, France
6 ECMWF, Shinfield Park, Reading, England

This study aims at assessing the consistency between different precipitable water vapour (PWV) datasets over Africa (between 10°S and 35°N). This region is characterized by large spatial and temporal variability of humidity but also by the scarcity of its operational observing network limiting our knowledge of the hydrological cycle. We inter-compare data from observing techniques such as ground-based Global Positioning System (GPS), radiosondes, AERONET sun photometers and SSM/I, as well as reanalyses from European Centre for Medium-Range Weather Forecasts (ERA40) and National Center for Environmental Prediction (NCEP2). The GPS data, especially, are a new source of PWV observation in this region. PWV estimates from nine ground-based GPS receivers of the international GPS network data are used as a reference dataset to which the others are compared. Good agreement is found between observational techniques, though dry biases of 12-14% are evidenced in radiosonde data at three sites. Reasonable agreement is found between the observational datasets and ERA40 (NCEP2) reanalyses with maximum bias < 9% (14%) and standard deviation < 17% (20%). Since GPS data were not assimilated in the ERA40 and NCEP2 reanalyses, they allow for a fully independent validation of the reanalyses. They highlight limitations in the reanalyses, especially at timescales from sub-daily to periods of a few days. This work also demonstrates the high potential of GPS PWV estimates over Africa for the analysis of the hydrological cycle, at timescales ranging between sub-diurnal to seasonal. Such observations can help studying atmospheric processes targeted by the African Monsoon Multidisciplinary Analysis (AMMA) project.

Keywords: GPS, precipitable water, Africa, Monsoon.